--- title: "awesome-ai-safety vs chatgpt-plugin-eval" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/giskard-ai-awesome-ai-safety-vs-llm-platform-security-chatgpt-plugin-eval" tools: ["giskard-ai-awesome-ai-safety", "llm-platform-security-chatgpt-plugin-eval"] --- # awesome-ai-safety vs chatgpt-plugin-eval *GraphCanon updated Aug 5, 2026* ## Verdict Pick awesome-ai-safety if awesome-ai-safety is a curated list of papers and technical articles focused on ensuring AI quality and safety across various machine learning domains including CV and NLP; pick chatgpt-plugin-eval if chatgpt-plugin-eval is an evaluation framework designed specifically to assess security, privacy, and safety concerns related to third-party plugins interfacing with large language models like ChatGPT. [awesome-ai-safety](https://giskard.ai) reports 220 GitHub stars, 39 forks, and 17 open issues, last pushed Apr 14, 2025. [chatgpt-plugin-eval](https://llm-platform-security.github.io/chatgpt-plugin-eval/) has 29 stars, 7 forks, and 1 open issues, last pushed Jul 29, 2024. Figures are from public GitHub metadata via [awesome-ai-safety's repository](https://github.com/Giskard-AI/awesome-ai-safety) and [chatgpt-plugin-eval's repository](https://github.com/llm-platform-security/chatgpt-plugin-eval). | | [awesome-ai-safety](/tools/giskard-ai-awesome-ai-safety.md) | [chatgpt-plugin-eval](/tools/llm-platform-security-chatgpt-plugin-eval.md) | | --- | --- | --- | | Tagline | A curated list of papers and technical articles on AI Quality & Safety | Framework for Evaluating Security in LLM Plugin Ecosystems | | Stars | 220 | 29 | | Forks | 39 | 7 | | Open issues | 17 | 1 | | Language | - | HTML | | Adopt for | awesome-ai-safety is a curated list of papers and technical articles focused on ensuring AI quality and safety across various machine learning domains including CV and NLP. | chatgpt-plugin-eval is an evaluation framework designed specifically to assess security, privacy, and safety concerns related to third-party plugins interfacing with large language models like ChatGPT. | | Persona | - | - | | Runtime | - | - | | License | Apache-2.0 | The license information for chatgpt-plugin-eval is unknown. | | Categories | Evaluation & Observability | Evaluation & Observability | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [awesome-ai-safety](/tools/giskard-ai-awesome-ai-safety.md) | [chatgpt-plugin-eval](/tools/llm-platform-security-chatgpt-plugin-eval.md) | | --- | --- | --- | | Days since push | 473d | 736d | | Open issues (now) | 17 | 1 | | Full report | [trust report](/tools/giskard-ai-awesome-ai-safety/trust.md) | [trust report](/tools/llm-platform-security-chatgpt-plugin-eval/trust.md) | ## Decision facts: awesome-ai-safety - **Pricing:** freemium - The repository is free to use under the Apache-2.0 license. However, external resources linked might have their own licensing terms or costs. - **Adopt for:** awesome-ai-safety is a curated list of papers and technical articles focused on ensuring AI quality and safety across various machine learning domains including CV and NLP. ## Decision facts: chatgpt-plugin-eval - **Pricing:** freemium - **Adopt for:** chatgpt-plugin-eval is an evaluation framework designed specifically to assess security, privacy, and safety concerns related to third-party plugins interfacing with large language models like ChatGPT. - **License detail:** The license information for chatgpt-plugin-eval is unknown. ## Choose when ### Choose awesome-ai-safety if… - Pricing: The repository is free to use under the Apache-2.0 license. However, external resources linked might have their own licensing terms or costs.. - Tags unique to awesome-ai-safety: ai, ai safety, ai-alignment, ai-quality. - When you need an aggregated source to explore topics such as AI alignment, robustness, fairness in ML models. ### Choose chatgpt-plugin-eval if… - Tags unique to chatgpt-plugin-eval: chatgpt, llm-plugins, privacy, security. - - When evaluating the security risks of integrating third-party services into your LLM platform through plugins - Leaner open-issue backlog (1). ## When NOT to use awesome-ai-safety - Not suitable if your requirement is a repository with hands-on coding examples rather than research papers and articles. - Avoid this resource if you are searching for datasets or tools that are not in the form of academic literature but practical utilities. - This platform may not provide sufficient guidance on hardware-specific testing, where practical constraints diverge from theoretical models. ## When NOT to use chatgpt-plugin-eval - - In cases where only generic, high-level security guidance is required without an in-depth framework analysis - - When the primary focus is on improving performance metrics rather than addressing specific security and privacy concerns of LLM plugins ## Common questions ### What is the difference between awesome-ai-safety and chatgpt-plugin-eval? awesome-ai-safety: A curated list of papers and technical articles on AI Quality & Safety. chatgpt-plugin-eval: Framework for Evaluating Security in LLM Plugin Ecosystems. See the comparison table for live GitHub stats and shared categories. ### When should I choose awesome-ai-safety over chatgpt-plugin-eval? Choose awesome-ai-safety over chatgpt-plugin-eval when Pricing: The repository is free to use under the Apache-2.0 license. However, external resources linked might have their own licensing terms or costs.; Tags unique to awesome-ai-safety: ai, ai safety, ai-alignment, ai-quality; When you need an aggregated source to explore topics such as AI alignment, robustness, fairness in ML models. ### When should I choose chatgpt-plugin-eval over awesome-ai-safety? Choose chatgpt-plugin-eval over awesome-ai-safety when Tags unique to chatgpt-plugin-eval: chatgpt, llm-plugins, privacy, security; - When evaluating the security risks of integrating third-party services into your LLM platform through plugins; Leaner open-issue backlog (1). ### When should I avoid awesome-ai-safety? Not suitable if your requirement is a repository with hands-on coding examples rather than research papers and articles. Avoid this resource if you are searching for datasets or tools that are not in the form of academic literature but practical utilities. This platform may not provide sufficient guidance on hardware-specific testing, where practical constraints diverge from theoretical models. ### When should I avoid chatgpt-plugin-eval? - In cases where only generic, high-level security guidance is required without an in-depth framework analysis - When the primary focus is on improving performance metrics rather than addressing specific security and privacy concerns of LLM plugins ### Is awesome-ai-safety or chatgpt-plugin-eval more popular on GitHub? awesome-ai-safety has more GitHub stars (220 vs 29). Stars measure visibility, not whether either tool fits your constraints. ### Are awesome-ai-safety and chatgpt-plugin-eval open source? Yes - both are open-source projects on GitHub. ### Where can I find alternatives to awesome-ai-safety or chatgpt-plugin-eval? GraphCanon lists graph-backed alternatives at [awesome-ai-safety alternatives](/tools/giskard-ai-awesome-ai-safety/alternatives) and [chatgpt-plugin-eval alternatives](/tools/llm-platform-security-chatgpt-plugin-eval/alternatives) ([awesome-ai-safety markdown twin](/tools/giskard-ai-awesome-ai-safety/alternatives.md), [chatgpt-plugin-eval markdown twin](/tools/llm-platform-security-chatgpt-plugin-eval/alternatives.md)), ranked by typed relationship edges rather than popularity votes. ### Is there a machine-readable version of this comparison? Yes. The markdown twin at [this comparison](/compare/giskard-ai-awesome-ai-safety-vs-llm-platform-security-chatgpt-plugin-eval.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, awesome-ai-safety or chatgpt-plugin-eval? awesome-ai-safety: Dormant. chatgpt-plugin-eval: Dormant. Compare maintenance labels, days since push, and release cadence in the trust section below - stars alone do not measure maintenance. ### Where are the full trust reports for awesome-ai-safety and chatgpt-plugin-eval? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [awesome-ai-safety trust report](/tools/giskard-ai-awesome-ai-safety/trust); [chatgpt-plugin-eval trust report](/tools/llm-platform-security-chatgpt-plugin-eval/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=giskard-ai-awesome-ai-safety`](/api/graphcanon/graph?tool=giskard-ai-awesome-ai-safety) - LLM index: [/llms.txt](/llms.txt) - Full corpus: [/llms-full.txt](/llms-full.txt) _GraphCanon - The knowledge graph for AI development. https://www.graphcanon.com/_